Optimization of multi-energy grid for smart stadiums based on improved mixed integer linear algorithm. (November 2022)
- Record Type:
- Journal Article
- Title:
- Optimization of multi-energy grid for smart stadiums based on improved mixed integer linear algorithm. (November 2022)
- Main Title:
- Optimization of multi-energy grid for smart stadiums based on improved mixed integer linear algorithm
- Authors:
- Lin, Yikai
Tang, Xiaojun
Fan, Xiaodong - Abstract:
- Abstract: Due to the relatively large uncertainty and high cost of the power generation of the multi-energy power grid system, the power grid optimization scheduling with these problems as the object of the solution needs to take more targeted optimization measures. The purpose of this paper was to study a better grid system optimization scheme, and an improved mixed integer linear algorithm was proposed. And based on this algorithm, the multi-energy power grid system of a smart stadium was optimized, and at the same time, the common particle swarm algorithm was used to optimize the power grid system to compare the effects. The experimental results showed that the total monthly power supply cost of the optimized power grid system based on the improved mixed integer linear algorithm was 2061.2 yuan, the maximum pollution reduction was 17.3%, and the power supply system working time was reduced by 4.2% on average. The total monthly power supply cost of the optimized power grid system based on particle swarm algorithm was 2126.1 yuan, the highest pollution reduction was 12.6%, and the power supply system working time was reduced by 5.7% on average. In contrast, it can be seen that compared with the optimization of particle swarm optimization, the optimized multi-energy grid system of smart stadiums based on the improved mixed integer linear algorithm reduces more power supply costs, increases the stability of power supply power, and reduces more pollution emissions, but it isAbstract: Due to the relatively large uncertainty and high cost of the power generation of the multi-energy power grid system, the power grid optimization scheduling with these problems as the object of the solution needs to take more targeted optimization measures. The purpose of this paper was to study a better grid system optimization scheme, and an improved mixed integer linear algorithm was proposed. And based on this algorithm, the multi-energy power grid system of a smart stadium was optimized, and at the same time, the common particle swarm algorithm was used to optimize the power grid system to compare the effects. The experimental results showed that the total monthly power supply cost of the optimized power grid system based on the improved mixed integer linear algorithm was 2061.2 yuan, the maximum pollution reduction was 17.3%, and the power supply system working time was reduced by 4.2% on average. The total monthly power supply cost of the optimized power grid system based on particle swarm algorithm was 2126.1 yuan, the highest pollution reduction was 12.6%, and the power supply system working time was reduced by 5.7% on average. In contrast, it can be seen that compared with the optimization of particle swarm optimization, the optimized multi-energy grid system of smart stadiums based on the improved mixed integer linear algorithm reduces more power supply costs, increases the stability of power supply power, and reduces more pollution emissions, but it is not effective in reducing system working time. … (more)
- Is Part Of:
- Energy reports. Volume 8(2022)
- Journal:
- Energy reports
- Issue:
- Volume 8(2022)
- Issue Display:
- Volume 8, Issue 2022 (2022)
- Year:
- 2022
- Volume:
- 8
- Issue:
- 2022
- Issue Sort Value:
- 2022-0008-2022-0000
- Page Start:
- 13417
- Page End:
- 13424
- Publication Date:
- 2022-11
- Subjects:
- Mixed integer linear algorithm -- Smart stadium -- Multi-energy grid -- Grid optimization
Power resources -- Periodicals
Energy industries -- Periodicals
Power resources
Periodicals
Electronic journals
621.04205 - Journal URLs:
- http://www.sciencedirect.com/science/journal/23524847/ ↗
http://www.sciencedirect.com/ ↗ - DOI:
- 10.1016/j.egyr.2022.09.070 ↗
- Languages:
- English
- ISSNs:
- 2352-4847
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 26109.xml